Objectives

Longitudinal studies of the relationship between neighborhood change and changes in crime typically focus exclusively on the net level of change in key socio-demographic characteristics.

Methods

We instead propose a demographic accounting strategy that captures the composition of neighborhood change: our measures capture which types of people are more likely to leave, stay, or enter the neighborhood. We use data for 3,325 tracts in the Southern California region over nearly two decades of 2000–2010 and 2010–2017 and construct flow measures based on race/ethnicity; the length of residence of owners and renters; the age structure.

Results

These flow measures improve the predictive power of the models—implying important theoretical insights. Neighborhoods with higher percentages of middle-aged residents who recently entered the neighborhood exhibit larger increases in violent and property crime. The relative stability of those in the highest crime-prone ages (aged 15–29) is associated with the largest increases in violent and property crime. The greater loss of Black and Asian residents decreased crime while moderate outflows of Latinos increased crime. The mobility of long- and short-term renters was related to crime changes.

Conclusions

This new technique will likely encourage further theoretical innovation for the neighborhoods and crime literature.

中文翻译：

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谁离开谁进入？邻里变化的流动措施和邻里犯罪的后果

目标

对邻里变化与犯罪变化之间关系的纵向研究通常只关注关键社会人口特征的净变化水平。

方法

相反，我们提出了一种人口统计策略来捕捉社区变化的构成：我们的措施捕捉到哪些类型的人更有可能离开、停留或进入社区。我们使用 2000-2010 年和 2010-2017 年近 20 年间南加州地区 3,325 个地区的数据，并根据种族/民族构建流量测量；业主和租户的居住时间；年龄结构。

结果

这些流量测量提高了模型的预测能力——暗示了重要的理论见解。最近进入该社区的中年居民比例较高的社区表现出暴力和财产犯罪的更大增加。犯罪率最高的年龄段（15-29 岁）的相对稳定性与暴力犯罪和财产犯罪的最大增加有关。黑人和亚裔居民的更大损失减少了犯罪率，而拉丁美洲人的适度外流增加了犯罪率。长期和短期租房者的流动性与犯罪变化有关。

结论

这种新技术可能会鼓励社区和犯罪文献的进一步理论创新。